**A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Technical Aspects**

**Tomasz Sikorski <sup>1</sup> , Michal Jasi ´nski 1,\* , Edyta Ropuszy ´nska-Surma <sup>2</sup> , Magdalena W˛eglarz 2,\* , Dominika Kaczorowska <sup>1</sup> , Paweł Kostyla <sup>1</sup> , Zbigniew Leonowicz <sup>1</sup> , Robert Lis <sup>1</sup> , Jacek Rezmer <sup>1</sup> , Wilhelm Rojewski 1, Marian Sobierajski 1, Jarosław Szyma ´nda <sup>1</sup> , Daniel Bejmert <sup>3</sup> , Przemysław Janik <sup>3</sup> and Beata Solak <sup>1</sup>**


Received: 6 May 2020; Accepted: 8 June 2020; Published: 15 June 2020

**Abstract:** The article presents calculations and power flow of a real virtual power plant (VPP), containing a fragment of low and medium voltage distribution network. The VPP contains a hydropower plant (HPP), a photovoltaic system (PV) and energy storage system (ESS). The purpose of this article is to summarize the requirements for connection of generating units to the grid. Paper discusses the impact of the requirements on the maximum installed capacity of distributed energy resource (DER) systems and on the parameters of the energy storage unit. Firstly, a comprehensive review of VPP definitions, aims, as well as the characteristics of the investigated case study of the VPP project is presented. Then, requirements related to the regulation, protection and integration of DER and ESS with power systems are discussed. Finally, investigations related to influence of DER and ESS on power network condition are presented. One of the outcomes of the paper is the method of identifying the maximum power capacity of DER and ESS in accordance with technical network requirements. The applied method uses analytic calculations, as well as simulations using Matlab environment, combined with real measurement data. The obtained results allow the influence of the operating conditions of particular DER and ESS on power flow and voltage condition to be identified, the maximum power capacity of ESS intended for the planed VPP to be determined, as well as the influence of power control strategies implemented in a PV power plant on resources available for the planning and control of a VPP to be specified. Technical limitations of the DER and ESS are used as input conditions for the economic simulations presented in the accompanying paper, which is focused on investigations of economic efficiency.

**Keywords:** virtual power plant; distributed energy resources; energy storage systems; grid codes; power systems; smart grids; prosumer; business model; economic efficiency; sensitivity analysis

#### **1. Introduction**

A Virtual Power Plant (VPP) is still an actual approach and there is not a standardized definition for the framework of a VPP in the literature. The origin of the terminology of "Virtual Power Plant" may be traced back to 1997, when S. Awerbuch, in the book "The Virtual Utility—Accounting, Technology and Competitive Aspects of the Emerging Industry" defined Virtual Utility as flexible cooperation of independent, market-driven actors that assures an efficient energy service expected by the consumers without the need for appreciating assets [1]. A VPP manages distributed energy resources (DER) named also distributed generation (DG) units [2]. For example, wind, solar and hydroelectric power generation units are interconnected. Managing them together enables them to be more effective [3–5].

A Virtual Power Plant, as an autonomous, intelligent unit equipped with effective and safe power flow control systems, consists of generators, loads and energy storage that is connected to the distribution network [6]. These devices are equipped with controllers, which usually power electronic converters that allow for power flow control [6]. Coordinating the work of the entire VPP is a difficult and demanding task. The system's architecture must not only enable power flow control but also ensure VPP protection—not only related to power system security but also cybersecurity. In Reference [7], VPP architecture based on a common information model (CIM) and IEC standard 61850 is shown.

There have recently been many attempts to integrate intelligent solutions in power systems. An interesting discussion related to microgrids and the VPP is presented in Reference [8]. Microgrids allow increasing the efficiency of the use of distributed energy sources and energy storage systems. It also allows for regulating the load. Microgrids can be connected to the power system or operate as a standalone system. VPP management is based on computer software that enables the integration of distributed sources. In systems connected to the distribution network, the value of the power generated by the generation sources, the operation of the energy storage and the response of the demand side are optimized. Several propositions proclaiming the idea of transforming microgrids to a virtual power plant have recently been discussed, among others in References [2,6]. Additionally, it is also worth mentioning a new topic called virtual microgrids, which can be recognized as software solutions and algorithms supporting the planning, design and operation of microgrids. As an example of the virtual microgrids, it is worth noting a prosumer cluster connection into virtual microgrids to obtain cost reduction [9] or energy peer-to-peer trading in virtual microgrids [10].

Due to the random nature of the generated power, a large number of independent renewable energy sources can lead to system stability problems and therefore the connecting of distant generation sources, loads and energy storage units into a VPP has many benefits [11]. Work [12] shows the possibility of using charging points for electric vehicles, as well as wind generation, in the VPP concept. It also presents power flow optimization while taking into consideration price, wind generation and electric vehicles. Paper [13] concerns VPP control power consumption for heating. The operation algorithm is based on the application of thermal mass to the building to defer power consumption from electric space heating.

There are many different aspects to VPP power flow control. The main goals correspond to economic aspects related to electrical energy trading. The VPP control algorithms predict energy storage charging at low energy prices, as well as discharging energy storage and the sale of energy at peak demand at high prices. Paper [14] presents a stochastic bi-level optimization model to maximize day-ahead profit and to minimize predicted real-time production and the consumption of imbalance charges. In Reference [15], the bidding strategy of a VPP is determined using mathematical models. Ref. [16] presents decentralized coordination of VPP units, considering both active and reactive power using the novel Lagrangian relaxation-based mechanism. The method takes into account the effect of flexible demand and prevents the creation of new demand peaks and troughs. Another aspect concerns optimizing the use of locally generated energy and using the right strategy for storing energy in energy storage [17,18]. Power flow in a VPP, due to technical aspects, can also be optimized. In Reference [19], the binary backtracking search algorithm (BBSA) is used to optimize power flow in a VPP in order to achieve a reduction of generation cost and power losses, as well as, to increase reliability. To achieve

the same goal, risk-constrained stochastic programming is used in Reference [20] and the Imperialist competitive algorithm is used in Reference [21]. A big problem in the modern generation can also be seen to be carbon dioxide emissions. In Reference [22], binary particle swarm optimization (BPSO) is used to solve the indicated issues.

However, technical issues cannot be overlooked when planning the different strategies for a VPP. For example, voltage levels at all points in the distribution network should be within the range allowed by the standards. The same applies to the values of currents in the transformer lines and windings. Cooperation between units included in the VPP, meeting these expectations, is presented in Reference [23]. Moreover, issues regarding the operation of the storage itself are also important. Studies on the impact of energy storage parameters on VPP strategy and performance are presented in References [24,25]. The crucial technical aim of the VPP is concentrated on the aggregation control of the number of distributed generation units, which are grid-connected close to consumers (end-users, households). The aggregation verification may be a centralized or not system supported by a logic control algorithm, as well as, a communication infrastructure [26]. The control strategies must concern reliability, uncertainty, stability, demand response, power quality, active and reactive power management, protection and balancing and reliability in various load circumstances [27–29].

Additionally, when technical aspects are indicated it is worth noticing the management entities—virtual power players issues. Virtual power players' aim is the generation and services remuneration or charging energy consumption. The diversity of players to expedite participation in the electricity markets is described in the literature [11,30,31]. Reference [32] proposes the methodology to DER management. The article includes resource scheduling, aggregation and remuneration. The aggregation process is realized by k-means algorithm. Clustering is realized for different approaches, that concerns tariffs definitions for the period of a week. Customer remuneration is realized in accordance to Portuguese time-of-use tariffs. The research corners twenty thousand consumers and five hundred distributed generation units. The paper [33] deal with the same issues. However, it is realized for 2592 operation scenarios. Those cases consider over 5 hundred DGs, over 20 thousand consumers and ten suppliers. The article [34] is another example of using clustering to prosumers aggregation. The article [35] presents the discussion of demand response in point economic pros and effectiveness. This article presents a sensitivity analysis of demand response prices for the virtual power player operation costs. Additionally, the analysis comparison of cost of distributed resources and demand-side response during facing supply unavailability. This calculation is performed in a real smart grid on buses with associated micro-production. This allows the creation of sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision-making process is found, according to players' characteristics. In addition to the technical aspects, selected issues concerning the roles of VPP partners are discussed in the accompanying paper [36]. Physical and financial streams between them are highlighted in point of the decision model which is concentrated on profits maximization. The results show that the number of distributed energy resources and the available storage capacity of battery energy storage has an impact on the economic efficiency of the VPP.

This article aims to study the technical aspects of integration of the above-mentioned units with an electrical power system (EPS) with regards to their prospective application in the VPP. The mentioned limitations are related to the regulation and protection procedures applied in the control of generation units and storage systems and also their possible influence on power system parameters. This article presents calculations and power flow of a real virtual power plant (VPP), containing a fragment of low and medium voltage distribution network. The model contains the hydropower plant (HPP), a photovoltaic system (PV), energy storage system (ESS). The problem is based on the identification of the limitations, which are dictated by the technical requirements of cooperation of power generation units and energy storage systems with the power system; the application of the simplified calculation, which is supported by precise simulation techniques so that the maximum power capacity of the planned energy storage system in the planed VPP can be indicated and the investigation of real

measurements of a photovoltaic power plant in order to reveal the impact of power control strategy on the potential of the resources integrated with the VPP. The presented review of VPP definitions and aims, as well as a summary of VPP projects, are the motivation for this paper. Additionally, to obtain the economic issues and impact on electricity marked firstly the technical requirements must be assured. The contribution of this paper covers the current gap of knowledge related to the VPP project which exhibits in the real case limitations of utilization the DER and ESS. For example, this paper provides the real case example of calculation and simulation focused on the determination of maximum power capacity of the ESS planned In terms of VPP efficiency and sensitivity, it is important to identify the maximum level of ESS power capacity that can be connected in the planned node to be installed in the selected network node. Results of presented investigations formulate margin condition for the VPP resources. Another example of the contribution of the paper to the current knowledge gap is the attempt to determine the influence of the power regulation strategies applied in PV plants on the real power range available for the VPP control strategies. Using the real measurement investigations it was shown that reactive power consumption implemented in the PV inverters reduces the energy volume potentially available for VPP form the PV installations. Mentioned examples constitute the limitation for the VPP project and can be adapted to other VPP investments.

The aim of this paper is to identify possible limitations in the development of the VPP which might be related to the regulation, protection and integration of power generation units with power systems. The mentioned problem can be seen to be a crucial issue, especially on the preliminary stage of the VPP concept and when different approaches for the economic strategies for VPP are created. After the introduction section, which highlights the main motivations of this paper, Section 2 presents a literature review of the technical aspects of VPP. This includes recent investigations regarding network integration, as well as a review of a selected real case of VPP realization. The aim of Section 2 is to identify current problems and solutions related to VPP and to provide the range of functionality of current VPP projects. Section 3 highlights the problems regarding the investigations presented in this paper. It has to be emphasized that technical aspects of DER and ESS, associated with the VPP, can be considered on several levels. Thus, Section 3 consists of the identification of codes and technical standards that define the requirements and permissible limits of electrical power system parameters and power quality, protection schemes and active and reactive power control issues applied for distributed energy resources. An additional element described in Section 3 is the energy storage control and limitations coming from the charging and discharging characteristics of energy storage systems. The revealed aspects can be treated as boundary conditions for the identification of their impact on VPP planning and operation strategies. The main investigations are presented in Section 4, which starts with a description of the topology of a medium voltage network in the area of the investigated VPP. The investigations are based on a real VPP project and present results considering the investigation of the cooperation of a 1 MW hydropower plant with 0.5 MW battery energy storage connected to the same node of medium voltage distribution network and impact of their operating condition on power flow and voltage level in observed network belonging to the VPP, (b) identification of maximum power capacity of battery energy storage which can be connected to considered node of the VPP as well as identification of general grid capacity of the investigated fragment of the distribution network to connect possible DERs/ESSs, (c) the identification of the impact of power control strategy applied in a PV power plant on resources available for the VPP. The maximum power capacity of the ESS is understood as the rated power of the ESS determined by requirements for power quality parameters of the grid and requirements for the integration of the generation units with power systems. In presented investigations, the storage capacity of the considered ESS is fixed and is used as a margin condition for the simulations. The storage capacity determines the ESS operability usually reflected by available time for charging and discharging. The selection of storage capacity of the ESS is usually based on specific aim functions considering selected intentions of using the ESS like economic aspects or islanding mode. The maximum power capacity of the ESS is restricted by the standards and regulations addressed to cooperation with the grids. The presented analysis is based on simulations conducted in Matlab

combined with real measurements. The initial condition for the calculation was based on the real measurements of load and generated power that represent a day of summer load peak demand. As a result of the investigation, the maximum power capacity of the considered ESS is identified with regards to the requirements for the permissible level of rapid voltage changes. Additionally, the impact of the power control strategy applied in a PV power plant on resources available for the VPP was also identified. In Section 5 a discussion about the influence of requirements for grid connection applicable to power generation units and its impact on limitation of the maximum power capacity of distributed energy resources and energy storage systems considered for planning operation of the VPP is provided in the broadest context. Section 6 presents the conclusions.

The identified limitations for the VPP, resulting from the technical aspects presented in this paper, are used as the input conditions for the economic investigations presented in the accompanying paper [36]. The paper presents the results of economic efficiency, including sensitivity analysis on price factors and DER production volumes, as well as the capacity of ESS.
